Main
Fishman et al. (2001) built a genetic linkage map of an interspecific cross between M. guttatus and M.nasutus. At that time, the \(F_2\) mapping population used (N=526) were genotyped for 174 markers. Based on this study, the authors found a genetic map of 2011-2096 cM Kosambi size, containing 174 marker loci distributed over 14 linkage group. Here we incorporate new genomic information onto the Fishman’s map in order to update the new loci information. By using a new data set of the same population with 418 markers, we founded 388 new loci and expanded the maps to a length of 2933.95 cM Kosambi. In relation to the Fishman et al. (2001) linkage map, our markers positions were mostly similar, however, we observed some inversions at some regions. Thereby, we also observed that some linkage groups were named differently (e.g. LG7 from Fishman were named as LG6 at ours) but having the same marker orders within them.
For more details about the procedures founded in this paper, also the strategies to build a genetic linkage map using OneMap R-package, please check our youtube video.
See also ou R-code used in this study, which is freely available to practice the concepts presented here. __________________________________________________________________________________________
Material and Methods
Genetic Material: A cross between Mimulus guttatus (outcrossing) x Mimus nasutus (selfing) originated an F\(_{2}\) population described in Fishman et al. (2001). This population was composed of 287 individuals genotyped with 418 markers. For more details see Fishman et al. (2001).
Genetic linkage map: We applied a segregation test to observe if there were distorted markers (Figure 1). The null-hypothesis (\(H_0\)) tested was segregation pattern of 1:2:1, as expected for an F\(_{2}\) population. To construct a linkage map, we made two-point tests with all markers, considering LOD score = 6 and the maximum recombination fraction \(\theta = 0.35\) and created a non-ordered sequence with all markers. Then, we used the function group to assign markers to linkage groups. We repeated this procedure three more times, changing the maximum recombination fraction (\(\theta_{max}\)) to 0.5 and 0.25 with LOD = 6, respectively, and 0.35 with LOD = 7.
Considering ad hoc information, the analysis continued with the strategy that resulted in the highest number of linkage groups. Makers were ordered between the 14 linkage groups by the function make_seq and then ordered the markers within each group with function order_seq. All the markers that were mapped in more than one position were added by the function make_seq, using the argument ‘force’, which assigned to the most probable position. After that, the same analysis was performed with non-distorted markers. By observing heatmaps for each linkage group, it was possible to check which markers should be removed because it doesn’t segregate as the expected recombination fraction pattern. These makers were removed using the function drop_markers. We followed the same pipeline described above, without those markers. Lastly, a final ordering was applied for each linkage group using ripple_seq function, considering a window size of five markers. We draw the genetic map with MapChart.
Software:The data was imported in a MAPMAKER file and the linkage map was built using OneMap package (Margarido et al, 2007). We draw the genetic maps using MapChart software (Vorrips et al 2002).
Results
The segregation pattern observed and the distorcion pattern is presented in Figure 1. A total of 14 linkage groups were formed (Figure 2), which agrees to the haploid number of chromosomes. The genetic map drawn with MapChart is presented in Figure 3.
Figure 1. Patterns of distorcion and segregation in Mimulus mapping population
Figure 2. Heatmaps describing marker order and recombination fraction over the 14 linkage groups of Mimulus guttatus.
